docs: def ensure_samples_is_ndim_ndarray(samples, name='bootstrap', ndim=2):
      """
      Ensures that `samples` is an `ndim` numpy array. Raises a helpful
      ValueError if otherwise.
      """
      assert isinstance(ndim, int)
      assert isinstance(name, str)
      if not isinstance(samples, np.ndarray) or not (samples.ndim == ndim):
          sample_name = name + "_samples"
          msg = "`{}` MUST be a {}D ndarray.".format(sample_name, ndim)
          raise ValueError(msg)
      return None